Gradient Descent Variants (SGD, Momentum, RMSprop, Adam) — Roadmap St…
How different optimizers navigate the loss surface differently
- Level: intermediate
- Estimated time: 2 days
- Roadmap: Deep Learning & Neural Networks
Before this step
Interview questions
- What problem does momentum solve that plain SGD struggles with?
- Why is Adam often the default optimizer choice?
Study resources
- Stochastic Gradient Descent, Clearly Explained!!! (Video) — StatQuest's widely-loved explanation of SGD and mini-batch gradient descent.
- Algorithms for Optimization (Article) — The official PyTorch documentation's reference for SGD, Adam and other optimizers.
Part of
- Neural Network Fundamentals — section
- Deep Learning & Neural Networks roadmap — the full learning path